University of Groningen

Contrasting glacial meltwater effects on post-bloom phytoplankton on temporal and spatialscales in Kongsfjorden, Spitsbergenvan de Poll, Willem; Kulk, Gemma; Rozema, Patrick; Brussaard, CPD; Visser, Ronald; Buma,AnitaPublished in:Elementa: Science of the Anthropocene

DOI:10.1525/elementa.307

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Citation for published version (APA):van de Poll, W., Kulk, G., Rozema, P., Brussaard, CPD., Visser, R., & Buma, A. (2018). Contrasting glacialmeltwater effects on post-bloom phytoplankton on temporal and spatial scales in Kongsfjorden,Spitsbergen. Elementa: Science of the Anthropocene, 60(1). https://doi.org/10.1525/elementa.307

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van de Poll, WH, et al. 2018. Contrasting glacial meltwater effects on post-bloom phytoplankton on temporal and spatial scales in Kongsfjorden, Spitsbergen. Elem Sci Anth, 6: 50. DOI: https://doi.org/10.1525/elementa.307

IntroductionThe Arctic is experiencing pronounced changes in cli-mate, which impact the conditions of phytoplankton growth (Arrigo, 2013). Eurasian Arctic regions such as the East Greenland Sea and the Barents Sea have experienced Atlantic inflow with higher heat content (Beszczynska-Möller, 2012; Soltwedel et al., 2015). Increased Atlantic advection and associated relatively high heat content has resulted in decreased wintertime sea ice formation on

the west coast of Spitsbergen (Kortsch et al., 2012). This process has also intensified melting of marine-terminat-ing glaciers on the west coast of Spitsbergen and on the east coast of Greenland (Straneo and Heimbach, 2013; Luckman et al., 2015). Atlantic advection in Kongsfjorden occurs in winter and summer, whereas its circulation in the fjord appears to be driven by along-fjord winds ( Sundfjord et al., 2017). Atlantic advection can introduce Atlantic phytoplankton and zooplankton populations into fjords like Kongsfjorden (Willis et al., 2008). These changes have transformed the conditions that shape biological activity and diversity on the west coast of Spitsbergen.

As sea ice formation in fjords becomes rare, glacial meltwater of marine-terminating glaciers and melt-water of terrestrial snow and ice become the primary sources of density stratification during spring and sum-mer (MacLachlan et al., 2007; van de Poll et al., 2016; Meire et al., 2017). Surface phytoplankton blooms in Kongsfjorden typically occur after meltwater-induced

RESEARCH ARTICLE

Contrasting glacial meltwater effects on post-bloom phytoplankton on temporal and spatial scales in Kongsfjorden, SpitsbergenWillem H. van de Poll*, Gemma Kulk*, Patrick D. Rozema*, Corina P. D. Brussaard†, Ronald J. W. Visser* and Anita G. J. Buma*,‡

Glacial meltwater discharge in fjords on the west coast of Spitsbergen is increasing due to climate change. The influence of this discharge on phytoplankton nutrient limitation, composition, productiv-ity and photophysiology was investigated in central (M) and inner (G) Kongsfjorden (79°N, 11°40’E). Freshwater influx intensified stratification during June 2015, coinciding with surface nutrient depletion. Surface nutrient concentrations were negatively correlated with stratification strength at station M. Here, nitrate addition assays revealed increasing N limitation of surface phytoplankton during the second half of June, which was followed by a pronounced compositional change within the flagellate-dominated phytoplankton community as dictyochophytes (85% of chl a) were replaced with smaller haptophytes (up to 60% of chlorophyll a) and prasinophytes (20% of chlorophyll a). These changes were less pronounced at station G, where surface phosphate, ammonium and nitrate concentrations were occasionally higher, and correlated with wind direction, suggesting wind-mediated transport of nutrient-enriched waters to this inner location. Therefore, glacial meltwater discharge mediated nutrient enrichment in the inner fjord, and enhanced stratification in inner and central Kongsfjorden. Surface chlorophyll a and water column pro-ductivity showed 3–4-fold variability, and did not correlate with nutrient limitation, euphotic zone depth, or changed taxonomic composition. However, the maximum carbon fixation rate and photosynthetic effi-ciency showed weak positive correlations to prasinophyte, cryptophyte, and haptophyte chlorophyll a. The present study documented relationships between stratification, N limitation, and changed phytoplankton composition, but surface chlorophyll a concentration, phytoplankton photosynthetic characteristics, and water column productivity in Kongsfjorden appeared to be driven by mechanisms other than N limitation.

Keywords: Arctic; phytoplankton; nutrient limitation; pigments; productivity; photophysiology; stratification; meltwater; Kongsfjorden

* Department of Ocean Ecosystems, Energy and Sustainability Research Institute Groningen, University of Groningen, Nijenborgh 7, 9747 AG Groningen, NL

† NIOZ Royal Netherlands Institute for Sea Research, Department of Marine Microbiology and Biogeochemistry, and Utrecht University, 1790 AB Den Burg, Texel, NL

‡ Arctic Centre, Faculty of Arts, University of Groningen, A-weg 30, 9718 GW Groningen, NL

Corresponding author: Willem H. van de Poll (w.h.van.de.poll@rug.nl)

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stratification and subsequently deplete macronutrient stocks as stratification continues throughout the sum-mer (Iversen and Seuthe, 2011). The timing of surface blooms in Kongsfjorden is variable, ranging from April to June (Hegseth and Tverberg, 2013). Stratification during spring and summer can be enhanced by the inflow of warmer Atlantic water. Moreover, freshwater runoff from land can be enhanced due to a rise in air temperature and an intensified hydrological cycle (Luckman et al., 2015; Bintanja and Selten, 2014; Carmack et al., 2016). Despite potential nutrient limitation of surface waters, these coastal fjords maintain relatively high productiv-ity levels during summer, of which the exact mecha-nisms remain poorly understood. In Kongsfjorden, low N:P ratios suggest nitrogen (N) as the most likely limit-ing element (Piquet et al., 2014; van de Poll et al., 2016). Moreover, N is suggested to be the primary limiting nutrient in the Arctic at large (Popova et al., 2010). Low nutrient concentrations are a driving factor in phyto-plankton succession, typically promoting smaller phy-toplankton species, which are more competitive under low nutrient concentrations due to higher surface area to volume ratios (Raven, 1998; Finkel 2001; Lindemann et al., 2016). Changes in phytoplankton size have the potential to directly impact higher trophic levels (Strom and Fredrickson, 2008). However, the extent to which changes in taxonomic composition due to nutrient limi-tation affect phytoplankton productivity, photophysiol-ogy, and biomass in natural phytoplankton communities is uncertain (Palmer et al., 2013).

The present study aimed to assess relationships between salinity stratification, nutrient limitation, and Arctic phytoplankton succession, productivity and pho-tophysiology. Therefore, post-bloom phytoplankton bio-mass, composition, and productivity were investigated in concert with environmental conditions in inner and central Kongsfjorden, allowing a comparison of variables in the meltwater gradient. Photosynthesis vs irradiance

experiments were used to evaluate photosynthetic charac-teristics and productivity at these stations. Nitrate addition assays were also performed to monitor nitrate limitation in central Kongsfjorden. We expected nitrate limitation at all stations in June due to strong stratification. We hypoth-esized that phytoplankton productivity would be lower at inner compared to central Kongsfjorden due to increased concentrations of glacial sediment near the marine-termi-nating glaciers. Colored dissolved organic matter (CDOM), which also influences optical properties of seawater, has been reported to be relatively low in Kongsfjorden (Pavlov et al., 2013).

MethodsSampling was conducted at two locations in Kongsfjorden, Spitsbergen (79°N, 11°40’E), during June 2015 (Figure 1). Station M (central Kongsfjorden, 238 m water depth) and station G (inner Kongsfjorden, 60 m water depth) were visited by boat on eight occasions. Seawater samples were collected at depths of 5.0, 12.5 and 25 m at stations M and G, using a 20-L Niskin bottle, and stored in the dark until processing in the laboratory (within 2 h). Water column profiles were obtained using a CTD (19+, Sea-Bird Elec-tronics) equipped with sensors for PAR [spherical, Licor, Sea-Bird Electronics] and fluorescence [Wetstar]). From the CTD data, the stratification index was calculated as the difference in potential density between depths of 5 and 50 m. Surface mixed layer depth was calculated using the depth of the first buoyancy frequency maximum observed in the upper 50 m. This criterion was found to be ecologi-cally relevant in coastal Antarctic waters (Carvalho et al., 2017). Irradiance attenuation (Kd) was calculated by linear regression of log-transformed PAR data, and the euphotic zone (defined as the depth interval down to 0.1% irradi-ance) was calculated as: Zeu (m) = –ln (0.001)/Kd. Air tem-perature and wind direction in Ny Ålesund were collected by the Alfred Wegener Institute Meteorological Surface Measurements.

Figure 1: Map of Kongsfjorden, Spitsbergen (79°N, 11°40’E). Indicated are stations M (central Kongsfjorden) and G (inner Kongsfjorden). Black lines indicate the main fronts of marine-terminating glaciers. DOI: https://doi.org/10.1525/elementa.307.f1

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NutrientsFive-mL subsamples (depths of 5, 12.5, 25 m) were filtered (0.2 µm Acrodisc, Pall) for nutrient analysis and stored at –20°C (phosphate, ammonium, nitrate plus nitrite) or 4°C (silicic acid). Nutrient analyses were conducted using a Traacs 800 autoanalyzer (Bran and Luebbe) according to Murphy and Riley (1962), Helder and De Vries (1979), and Grasshoff (1983). Detection limits were 0.01, 0.03, 0.02, and 0.26 µM for phosphate, ammonium, nitrate plus nitrite, and silicic acid, respectively.

MicroscopySubsamples (5 m, n = 10) for light microscopy (100 mL) from stations M (n = 8) and G (n = 2) were fixed with 1.5 mL Lugol’s iodine solution and stored at 4°C in the dark until analysis using an Olympus IMT-2 inverted micro-scope (Utermöhl technique; Edler and Elbrächter, 2010). The phytoplankton community was semi-quantitatively observed (i.e., not counted) using categories for dictyo-chophytes, small flagellates, dinoflagellates, and diatoms in settled sample volumes of 5 and 50 ml. Microzooplank-ton was counted and classified as total ciliates, and small and large dinoflagellates.

Phytoplankton pigment and CHEMTAX analysisPigment samples (5.0, 12.5, 25 m) were obtained by mild vacuum filtration (0.2 bar) of 4–10 L seawater on 47 mm GF/F (Whatman) filters. Afterwards, filters were snap-fro-zen in liquid nitrogen and stored at –80°C until pigment analysis by high performance liquid chromatography (HPLC). For HPLC analysis, filters were freeze-dried for 48 h before extraction in 90% acetone (v/v) for 48 h (4°C, darkness) (van Leeuwe et al., 2006). Pigments were sepa-rated by HPLC (Waters 2695) with a Zorbax Eclipse XDB-C8 column (3.5 µm particle size), using the method of Van Heukelem and Thomas (2001). Detection was based on retention time and diode array spectroscopy (Waters 996) at 436 nm. Pigments were quantified manually using standards for all used pigments (DHI lab products). Abso-lute and relative abundances of phytoplankton groups were assessed by CHEMTAX (version 1.95) (Mackey et al., 1996), which uses factor analysis and steepest descent algorithm to partition pigments between six groups using initial pigment ratios (Table S1). Included groups were based on microscopic observations: prasinophytes, hap-tophytes, pelagophytes, dictyochophytes, dinoflagellates, and cryptophytes. Diatoms were not observed in light microscopy samples and therefore were not included in CHEMTAX. Results of the haptophyte and pelagophyte sub-groups were pooled (the latter was of minor impor-tance) and were denoted as ‘haptophytes’. The pigment data set was split across sampling time and sample depth, resulting in four CHEMTAX bins: samples collected from 5 to 18 June at depths of 5–12.5 m (bin 1, n = 26) and 25 m (bin 2, n = 15). A second pair of bins contained samples collected between 22 and 29 June at depths of 5–12.5 m (bin 3, n = 21) and 25 m (bin 4, n = 6). All pigments were allowed to vary during CHEMTAX analysis (chl a: 100%, other pigments: 500%). Initial and final pigment ratios are presented in Table S1.

Depth-integrated chl a (upper 50 m) was calculated using reconstructed vertical chl a profiles (Figure S1E, F) based on HPLC determined chl a and chl a fluorescence profiles. The chl a fluorescence profiles (5–50 m) were calibrated against HPLC determined chl a. Linear relation-ships of 5 and 12.5 m (used between 5 and 19 m) were different from those obtained at 25 m (used below 19 m). Furthermore, relationships in the upper 12.5 m during 5 to 22 June and 25 to 29 June were different. We assumed equal chl a concentrations in the upper 5 m, regardless of chl a fluorescence, which was assumed to be influenced by non-photochemical quenching.

Nitrate addition assay (station M only)Nitrate addition assays were performed using 5-m sam-ples from station M that were collected on eight occa-sions during the course of June 2015. Subsamples (175 ml) were incubated in acid-washed transparent plastic culture flasks with (nine replicates) and without (nine replicates) nitrate addition (11 µM final concentration) in a cooled incubator (3.5°C) under 20 µmol photons m–2 s–1 of continuous irradiance (250 W MHNTD lamp, Philips, combined with four layers of neutral density screen). The subsamples were not pre-filtered to exclude grazers. Pig-ment samples were obtained after 60 h of incubation by mild vacuum filtration (0.2 bar) of 150 ml seawater on 25-mm GF/F (Whatman) filters. Chl a concentration was determined using HPLC as described above. Specific growth rates (µ, d–1) were calculated by fitting chl a con-centrations at the start and end of the incubation period with an exponential function. The differences between the average final chl a concentration of nitrate additions and controls were used as a measure for nitrogen limita-tion (N-limitation index).

Photosynthesis-irradiance (P-E) curvesPhotosynthesis-irradiance (P-E) incubations were per-formed using a modified photosynthetron method (Lewis and Smith, 1983, Rozema et al., 2017). Subsamples (20 ml) collected at 5 m depth at stations M (n = 8) and G (n = 8) were spiked with 10 µl of 0.37 MBq NaH14CO3 and incu-bated for 3 h at 21 light intensities (15–1500 µmol pho-tons m–2 s–1, provided by an Osram power ball HCl-TT 250 W lamp) in 60-ml transparent PET vials in a cryostat-cooled incubator (at in situ temperature). Afterwards, samples were filtered onto 0.4 µm pore size polycarbonate filters (25 mm, Milipore), and acidified by HCl fumes under active air filtration (15 min) to remove excess 14C-bicarbonate. Filters were then transferred to 20-ml transparent scintil-lation vials (PET) and 10 mL of Ultima Gold (Perkin Elmer, the Netherlands) scintillation liquid was added. Vials were vortexed and counted (5 min) after 2 days using a Tri-Carb 2000 CA scintillation counter (Packard). For each P-E incu-bation three t = 0 samples (14C spiked samples that were directly filtered and acidified) and three total activity sam-ples (100 µl subsamples added to 10 ml of scintillation fluid with 200 µl ethanolamine) were prepared. Carbon incorporation calculations assumed dissolved inorganic carbon (DIC) concentrations of 2100 µmol kg–1. The pho-tosynthetic efficiency (α: mg C mg chl a–1 h–1(µmol pho-

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tons m–2 s–1)–1), maximum carbon fixation rate (Pmax: mg C mg chl a–1 h–1), and photoinhibition (β: mg C mg chl a–1 h–1 (µmol photons m–2 s–1)–1) were calculated using the method of Platt et al. (1980). The photoacclimation index was calculated as Ek = Pmax/α (µmol photons m–2 s–1). P-E curves combined with reconstructed vertical chl a profiles (Figure S1E, F), light attenuation (Kd) and incident photo-synthetically active radiation (PAR) (1 h average, collected by the Baseline Surface Radiation Network, Ny Ålesund, Figure S2A) were used to calculate the daily water column productivity in the euphotic zone (mg C m–2 d–1). These calculations assumed identical photophysiological charac-teristics in the euphotic zone.

StatisticsLinear correlations (Pearson Product Moment) were used to investigate relationships between environmental data. Relationships between environmental and biological data were investigated using non-linear correlations (Spearman Rank Order). Correlations were considered significant at p < 0.05. Means are reported with standard deviations. Differences between nitrate addition and controls were tested for significance using a Mann-Whitney U test for each of these assays.

Non-metric multidimensional scaling (NMDS) was applied to the absolute abundances of the phytoplank-ton groups as estimated by CHEMTAX of the upper 12.5

m (Ramette, 2007). Before analyses, duplicates were aver-aged and the absolute abundances were transformed using a Box-cox transformation. City-block distances were calculated, as the different groups greatly varied in their scale of change. Clustering was proposed relating to the changes in the community. Both within clusters (between stations) and between clusters (between temporal inter-vals) were tested for similarity using NP-MANOVAs using the same distance measure (Anderson, 2001). The p val-ues were corrected for multiple testing by a Bonferroni correction (Dunn 1961). NMDS and NP-MANOVAs were conducted using Past 2 (Hammer et al., 2001).

ResultsHydrographical conditions at stations M and GA pronounced difference in potential density between 5 and 50 m established during June at stations M and G (Figure 2A). The stratification index increased over time at both stations. Surface salinity (5 m; Figure S1A, B) showed a negative correlation with the stratification index (stations M and G combined, ρ = –0.97, p < 0.0001). Surface mixed layer depth in June averaged 9 ± 8 and 5 ± 4 m at stations M and G, respectively (results not shown). Sea surface temperature (5 m) increased from 3.2 ± 0.6 (aver-age before June 15) to 5.2 ± 1.0°C at station M during the second half of June (Figure 2B; Figure S1C, D), but showed less temporal variability at station G (average: 3.2 ± 0.5°C).

Figure 2: Environmental conditions. Stratification strength (potential density difference between depths of 5 and 50 m) at stations M and G during June 2015 (A). Surface temperature (5 m) at stations M and G, and daily averaged air temperature (Ny Ålesund) (B). Euphotic zone depth (down to 0.1% irradiance) at stations M and G (C). Wind direction (24-h average before sampling) measured in Ny Ålesund (D). The symbol x indicates hourly averaged wind direction during this period. DOI: https://doi.org/10.1525/elementa.307.f2

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Mean daily air temperature in Ny Ålesund increased from 2.2 to 5.2°C during the course of June (Figure 1B). The euphotic zone (Zeu) was deeper at station M than at station G on every sampling occasion, and shallowed over time at stations M (45 ± 9.9 m to 19 m) and G (33 to 10 m) (Fig-ure 2C). Wind direction (24 h average prior to sampling) changed from northwest (321°) to southeast (119°) June 5 to 15, back to northwest (282°) June 18 to 25, and to southeast again at the end of June (Figure 2D). Mean wind speed in Ny Ålesund in June was 3.3 ± 2.0 m s–1. Salinity at 75 m at station M showed a negative correlation with wind direction (ρ = –0.71, p = 0.037).

Nutrient concentrations at stations M and GSurface (5 m) concentrations of phosphate, ammonium, nitrate plus nitrite, and silicic acid were low in June. Nitrate:phosphate molar ratios at stations M and G were

low (mean for upper 25 m: 2.3 ± 1.6 and 4.5 ± 2.4 for M and G, respectively) (data not shown). Surface nutri-ent concentrations showed different temporal dynamics at stations M and G (Figure 3). Surface phosphate and nitrate plus nitrite concentrations correlated negatively with stratification strength at station M but not at station G (Table 1). Surface phosphate, ammonium, and nitrate plus nitrite concentrations showed negative correlations with wind direction at station G but not at station M. Surface nutrient concentrations (except silicic acid) at both stations correlated negatively with surface temper-ature (Table 1). Nutrient concentrations (except silicic acid) at 25 m were higher than those at 5 m (Figure 3). Phosphate, ammonium, and nitrate plus nitrite con-centrations at 25 m increased until June 15 at stations M and G, followed by declines, which were stronger at station M.

Figure 3: Nutrient concentrations. Phosphate (A, B), ammonium (C, D), nitrate plus nitrite (E, F), and silicic acid (G, H) concentrations in surface water (5 m) (A, C, E, G) and at 25-m depth (B, D, F, G) at stations M and G during June 2015. Surface nutrient concentrations at station M are from two individual water samples; other measurements, from a single sample. Note the difference in scale between panels A, C, E, and B, D, F. DOI: https://doi.org/10.1525/elementa.307.f3

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Phytoplankton chlorophyll a and productivity at stations M and GSurface and depth-integrated chl a concentrations at stations M and G showed different temporal dynamics (Figure 4A, B; Figure S1E, F). At station M depth-inte-grated chl a (upper 50 m) increased to a maximum of 84 mg m–2 on June 25, whereas surface chl a peaked on June 15. At station G, surface and depth-integrated chl a decreased until June 15, increased towards June 22, and decreased afterwards (Figure 4B). Depth-integrated (0–50 m) chl a at station M correlated positively to strati-fication strength and surface temperature (Table 2). Surface chl a at station G correlated positively to wind direction, which was not observed at station M. Tempo-ral dynamics of daily productivity in the euphotic zone (PPZeu) were comparable (average for June: 528 ± 246 mg C m–2 d–1) for stations M and G (Figure 4C). PPZeu was vari-able and peaked between June 18 and 22 (average M, G: 901 ± 51 mg C m –2 d–1) and declined afterwards to 348 ± 109 mg C m–2 d–1. Calculated productivity rates in the upper 5 m of the water column were higher at station G as compared to M, except on June 15 and 29 (Figure S2B, C). PPZeu showed a positive correlation with surface temperature at station G.

Nitrate limitation assays at station MThe difference in accumulated chl a between nitrate addition and control assays increased during the eight assays performed in June (Figure 5). The assays showed significant N limitation during the second half of June (p < 0.001), with higher chl a-based growth rates during nitrate addition from June 15 onwards, as compared to controls without nitrate addition. Prior to June 15, growth rates (mean of controls and N additions) were 0.83 ± 0.2 d–1. From June 15 onwards, growth rates aver-aged 0.24 ± 0.2 d–1 in control assays, and 0.54 ± 0.1 d–1 during N addition. The N-limitation index ( Figure 5) showed positive correlations with stratification strength (ρ = 0.833, p < 0.01) and depth-integrated chl a at sta-tion M (Table 2).

Phytoplankton composition at stations M and GLight microscopy revealed dominance of the flagellate Dictyocha speculum (Dictyochophyceae, 10–15 µm cell diameter) until June 18 (data not shown). Afterwards, this species declined in abundance, whereas the number of smaller (2–5 µm) unidentified flagellates increased. Furthermore, cryptophytes and small dinoflagellates (<35 µm) were observed more frequently in compari-

Table 1: Pearson correlation coefficientsa between surface water (5 m) concentrations of phosphate, ammonium, nitrate plus nitrite (NO3 and NO2), and silicic acid and stratification strength, surface water (5 m) temperature, and wind direction. DOI: https://doi.org/10.1525/elementa.307.t1

Environmental variable Station Surface water (5 m) nutrient concentration

Phosphate Ammonium NO3 + NO2 Silicic acid

StratificationM –0.67 (0.01)* –0.41 (0.11) –0.56 (0.03)* 0.20 (0.46)

G –0.51 (0.22) –0.46 (0.26) –0.18 (0.66) 0.14 (0.72)

TemperatureM –0.76 (0.00)* –0.50 (0.05) –0.72 (0.00)* 0.024 (0.93)

G –0.78 (0.02)* –0.81 (0.01)* –0.91 (0.00)* –0.64 (0.07)

Wind directionbM –0.15 (0.58) –0.04 (0.89) –0.10 (0.72) –0.03 (0.91)

G –0.83 (0.01)* –0.83 (0.01)* –0.71 (0.04)* 0.12 (0.75)

a Asterisks indicate significant relationships; p values are shown in parentheses.b 24-h average prior to sampling.

Table 2: Spearman rank correlation coefficientsa between surface water (5 m) chlorophyll a (chl a), depth-integrated chl a (0–50 m), and productivity in the euphotic zone (PPZeu) and stratification strength, surface water (5 m) temperature, wind direction, and N-limitation index. DOI: https://doi.org/10.1525/elementa.307.t2

Environmental variable Station Chl a (5 m) Chl a (0–50 m) PPZeu

StratificationM 0.24 (0.54) 0.79 (0.00)* 0.17 (0.53)

G 0.43 (0.30) 0.57 (0.15) 0.11 (0.78)

TemperatureM –0.19 (0.62) 0.98 (0.00)* 0.29 (0.28)

G 0.33 (0.39) 0.57 (0.15) 0.89 (0.00)*

Wind directionb M –0.38 (0.32) 0.00 (0.93) –0.17 (0.53)

G 0.71 (0.04)* 0.50 (0.27) 0.25 (0.55)

N-limitation indexc M 0.17 (0.66) 0.74 (0.00)* 0.45 (0.08)

a Asterisks indicate significant relationships; p values are shown in parentheses.b 24-h average prior to sampling.c Available for station M only.

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son to early June. Diatoms were absent in all micros-copy samples. Microzooplankton changed in concert with photosynthetic phytoplankton at station M. Ciliate concentrations were maximal on June 5 (5080 cells L–1) and declined on June 11 (average 817 ± 449 cells L–1). Gyrodinium spirale (Dinophyceae) averaged 1705 ± 835 cells L–1 until June 15 and increased to 8660 cells L–1 on June 29, whereas large unidentified dinoflagellate con-centrations averaged 20 ± 21 cells L–1. CHEMTAX analy-sis showed a dominance of dictyochophyte chl a until June 18 ( average 86% of chl a) and a decline of this taxonomic group afterwards (Figure 6A). The decline in surface dictyochophytes was more pronounced at sta-

tion M as compared to G. By the end of June, the relative abundance of dictyochophytes reduced to less than 1% of chl a at station M. In contrast, surface prasinophytes, cryptophytes, and haptophytes increased in relative and absolute abundance after June 18 at stations M and G (Figure 6C, E, G). Absolute prasinophyte, cryptophyte, and haptophyte chl a showed positive correlations to stratification strength and the N-limitation index (station M only) (Table 3). Relative cryptophyte abundance at 25 m decreased at stations M and G over time (Figure 6F). Peridinin-containing dinoflagellates showed a low rela-tive abundance, contributing between 0.5 and 3% to chl a (not shown).

Clustering (NMDS) showed significant grouping of sta-tions M and G from June 5 to 11, where samples of M and G were not different (Figure S3). A second cluster was observed for M and G from June 22 to 29 that was signifi-cantly different from the first cluster (pseudo-F = 23.75, p < 0.001). Within the second cluster, samples of M and G were significantly different (Bonferroni corrected Manhattan distance, F = 3.856, p < 0.05).

Figure 4: Phytoplankton chlorophyll a and productiv-ity. Surface water concentrations of chlorophyll a (chl a 5 m) (A), depth-integrated chl a (B), and productivity in the euphotic zone (Zeu) (C) at stations M and G dur-ing June 2015. Surface chl a concentrations at station M are from two individual water samples; other meas-urements, from a single sample. Productivity was calcu-lated using carbon fixation characteristics presented in Figure 7. DOI: https://doi.org/10.1525/elementa.307.f4

Figure 5: Nitrate addition assays. Chlorophyll a-based specific growth rates (d–1) (mean ± standard deviation), with (+ nitrate) and without (control) nitrate addition, as observed during eight consecutive nitrate addition experiments conducted with surface water (5 m) sam-ples collected at central Kongsfjorden (A). Error bars indicate standard deviation of the mean (n = 9 in all cases). N-limitation index: difference in chl a concentra-tion between nitrate additions and controls after 60 h of incubation (B). Results are shown on the collection dates of the surface samples (5 m) at station M. DOI: https://doi.org/10.1525/elementa.307.f5

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Carbon fixation characteristics and photophysiology at stations M and GMaximum carbon fixation rate (Pmax) increased at station M after June 15 from 1.5 ± 0.5 to 2.7 ± 0.4 µg C chl a–1 h–1, whereas this increasing trend was not observed at station G (mean of 2.1 ± 0.5 µg C chl a-–1 h–1) (Figure 7A). The pho-tosynthetic efficiency (α) was higher at station G compared

to station M (except on June 29) (Figure 7B). Photosyn-thetic efficiency increased, whereas the photoacclimation index (Ek) decreased during the course of June (Figure 7C). This decrease was most pronounced at station M, where Ek declined from 125 ± 20 (until June 15) to 93 ± 5 µmol photons m–2 s–1. At station G the average Ek was 81 ± 22 µmol photons m–2 s–1. The Ek at station M correlated nega-

Table 3: Spearman rank correlation coefficientsa between surface water (5 m) prasinophyte, cryptophyte, dictyochophyte, and haptophyte chlorophyll a (chl a) and surface water (5 m) temperature, stratification strength, euphotic zone depth and N-limitation index. DOI: https://doi.org/10.1525/elementa.307.t3

Environmental variable Chl a (absolute amount) by phytoplankton taxon

Prasinophyte Cryptophyte Dichtyochophyte Haptophyte

Stratification 0.81 (0.00)* 0.79 (0.00)* –0.13 (0.55) 0.72 (0.00)*

Temperature 0.52 (0.01)* 0.42 (0.04)* –0. 21 (0.32) 0.41 (0.05)*

Euphotic zone –0.53 (0.01)* –0.45 (0.03)* –0.09 (0.67) –0.51 (0.01)*

N-limitation index 0.79 (0.00)* 0.83 (0.00)* –0.16 (0.55) 0.81 (0.00)*

a Correlations were with stations M and G combined except for the N-limitation index, which was determined at station M only. Asterisks indicate significant relationships; p values are shown in parentheses.

Figure 6: Relative abundance of phytoplankton taxonomic groups. Relative abundance (fraction of chlorophyll a) of dictyochophytes (A, B), haptophytes (C, D), cryptophytes (E, F), and prasinophytes (G, H) at stations M and G, shown for samples collected at depths of 5 m (A, C, E, G) and 25 m (B, D, F, H). Surface relative abundance at station M are from two individual water samples; other measurements, from a single sample. DOI: https://doi.org/10.1525/elementa.307.f6

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tively to the N-limitation index, and positively to euphotic zone depth. The α and Pmax showed weak positive correla-tions with relative prasinophyte, cryptophyte, and hapto-phyte abundance, and negative correlations with relative dictyochophyte abundance (Table 4). In addition, α corre-lated positively to the stratification index (Table 4). The Ek at station M correlated negatively to the N-limitation index and positively to euphotic zone depth (Table 4). Photoin-hibition (β) averaged 0.0014 ± 0.0016 mg C mg chl a–1 h–1 (µmol photons m–2 s–1)–1 and did not show a temporal trend.

DiscussionThe surface phytoplankton community experienced nutri-ent depletion in June 2015, with chl a concentrations that were typical for the post-bloom period in June (Hegseth and Tverberg, 2013; van de Poll et al., 2016). Furthermore, the higher ammonium than nitrate concentrations that we observed in June suggest that productivity in Kongs-fjorden was regulated by remineralization of nutrients. These nutrient conditions coincided with a phytoplankton community that was dominated by flagellates and their grazers, which were previously shown to be an impor-tant component of post-bloom phytoplankton in Kongs-fjorden (Iversen and Seuthe, 2011; Seuthe et al., 2011). In the present study, stratification mediated by freshwater was strong and further increased during June. The aver-age potential density difference between 5 and 50 m was 45-fold higher in June 2015 compared to observations in April 2014 (van de Poll et al., 2016). Stratification strength in June was comparable to stratification in the oligotrophic North East Atlantic but lower than maximum stratification strength in the Canada Basin (van de Poll et al., 2013; Tremblay et al., 2015).

The nitrate addition assays showed that surface phytoplankton growth in central Kongsfjorden was lim-ited by nitrogen from June 15 onwards, coinciding with increasing stratification. N limitation was also suggested by the overall low inorganic N:P ratios, although a temporal trend in N:P was not observed. Decreasing growth rates of controls and nitrate addition treatments, combined with low phosphate and silicic acid concentrations, could signal

Figure 7: Characteristics of phytoplankton carbon fixation. Maximum carbon fixation rate (A), photosyn-thetic efficiency (B), and photoacclimation index (C), in surface water samples (5 m) at stations M and G. DOI: https://doi.org/10.1525/elementa.307.f7

Table 4: Spearman rank correlation coefficientsa between maximum carbon fixation rate (Pmax), photosynthetic efficiency (α), and photoacclimation index (Ek) at 5 m depth and stratification strength, surface temperature, euphotic zone depth, N-limitation index, and relative abundance of prasinophyte, cryptophyte, dictyochophyte, and haptophyte chl a. DOI: https://doi.org/10.1525/elementa.307.t4

Variable Pmaxα Ek

Stratification 0.51 (0.05) 0.58 (0.02)* –0.44 (0.10)

Temperature 0.26 (0.33) 0.03 (0.90) 0.08 (0.80)

Euphotic zone –1.3 (0.63) –0.42 (0.12) 0.56 (0.03)*

N-limitation index 0.29 (0.46) 0.52 (0.16) –0.81 (0.01)*

Prasinophyte chl a (fraction) 0.54 (0.03)* 0.55 (0.03)* –0.19 (0.46)

Cryptophyte chl a (fraction) 0.56 (0.03)* 0.67 (0.005)* –0.37 (0.16)

Dichtyochophyte chl a (fraction) –0.54 (0.03)* –0.65 (0.01)* 0.32 (0.22)

Haptophyte chl a (fraction) 0.48 (0.06)* 0.62 (0.01)* –0.34 (0.19)

a Correlations were with stations M and G combined except for the N-limitation index, which was determined at station M only. Asterisks indicate significant relationships; p values are shown in parentheses.

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the possibility of phosphate and silicic acid co-limitation during the second half of June.

The onset of N limitation as detected by the assays was followed by a pronounced change in phytoplankton taxo-nomic composition from a dictyochophyte-dominated phytoplankton community to one dominated by hap-tophytes and prasinophytes, with subsequent changes in cell size (dictyochophytes: 10–15 µm; haptophytes: 5 µm; prasinophytes: 2 µm). Smaller phytoplankton species are believed to be more competitive during low nutrient concentrations due to a high surface area to volume ratio (Raven, 1998; Li et al., 2009; Finkel 2001; Lindemann et al., 2016). The change in phytoplankton composition showed considerable delay compared to the onset of N limitation. This delay may be related to different conditions during the assays in comparison to in situ conditions, such as grazing pressure from large zooplankton. However, the photoacclimation index and daily experienced irradiance showed that irradiance conditions during the assays were 4–5-fold lower than those experienced at 5-m depth in central Kongsfjorden. Given the relatively low light condi-tions used in the assays, the observed response to nitrate enrichment should be considered conservative, and thus to underscore the severity of nitrate limitation in situ in the surface waters.

The pronounced change in phytoplankton taxonomic composition was not clearly reflected in surface chl a con-centrations, which were variable (up to 4-fold differences) and showed no relationship with stratification strength or N limitation at station M. Thee findings are in line with observations in the Canada Basin, where mean surface chl a did not change in relation to decreasing nutrient con-centrations, while changes in the phytoplankton commu-nity were evident on a temporal scale (Li et al., 2009). In the present study, stratification coincided with increased depth-integrated chl a at station M and reduced nutrient concentrations at 25 m. Chl a accumulation at depth at station M was around the base of the euphotic zone and therefore exerted a limited effect on productivity. In con-trast, reduced light penetration due to glacial sediment presumably prevented the build-up of depth-integrated chl a at station G, thereby maintaining higher nutrient con-centrations close to the surface. Glacial melting at inner Kongsfjorden coincides with sediment influx, thereby increasing light attenuation (Piquet et al., 2014; van de Poll et al., 2016; this study). This effect is widely believed to limit productivity in inner Kongsfjorden (Wiencke and Hop, 2016). However, our productivity estimates did not show consistent differences in water column productivity between inner and central Kongsfjorden, in spite of a shal-lower euphotic zone at station G. Observations in April and May showed a stronger contrast in irradiance attenu-ation and hydrographical conditions between central and inner Kongsfjorden (van de Poll et al., 2016), as com-pared to June. Our observations were prior to the peak sediment and glacial meltwater discharge in Kongsfjorden (July and August).

Surface nutrient concentrations at station G were occasionally higher than those at station M, and showed dynamics that correlated with wind direction. Increased summertime nutrient concentrations at inner compared

to central Kongsfjorden were previously observed in July 2014, but not in 2013 (Fransson et al., 2016). This phe-nomenon was suggested to be caused by upwelling of fresh glacial meltwater (Lydersen et al., 2014). In the pre-sent study, the nutrient-enriched water may have been transported to our sampling site at inner Kongsfjorden due to out-of-fjord winds from the southeast. Moreover, a chl a peak was observed three days after the nutri-ent spike, suggesting that nutrient-enriched surface water triggered elevated biological activity at inner Kongsfjorden. Furthermore, changes in phytoplankton composition were less pronounced at station G as com-pared to M, suggesting a reduced effect of N limitation at the former site. Our data do not show relationships that point to wind-related nutrient enrichment effects beyond inner Kongsfjorden. Nevertheless, surface chl a at station M peaked on the day of enrichment at station G. The nega-tive correlation of salinity at depth at station M and wind direction suggests that the same process caused advection of deep saline water, coinciding with increased nutrient concentrations at 25 m. Possibly, episodic wind-mediated transport of nutrient-enriched water masses could explain the patchiness of chl a concentrations and productivity during the stratified summer period in Kongsfjorden.

Similar to surface chl a, water column productivity showed 4-fold differences on temporal scales, but no sig-nificant trends in relation to N limitation, stratification, or taxonomic changes. Carbon fixation characteristics showed variability that was weakly correlated to phytoplankton composition. The overall effect of these changes on water column productivity appeared to be limited. The differ-ences in chl a-specific carbon fixation characteristics may arise from cell size and changes in cellular chl a related to chl a self-shading. Palmer et al. (2013) reported no change in chl a-specific maximum photosynthetic rates when comparing the characteristics of nutrient-limited surface and irradiance-limited sub-surface chlorophyll maxima of coastal and open ocean phytoplankton in the Chukchi and Beaufort Sea. In contrast, higher chl a-specific maxi-mum photosynthetic rates were associated with diatoms as compared to flagellate-dominated communities in the Labrador Sea (Fragoso et al., 2016). We observed a trend of increasing photosynthetic efficiency (and decreasing pho-toacclimation index) in response to decreasing irradiance in Kongsfjorden. This trend may represent the classical photoacclimation response of increased light harvesting efficiency under reduced irradiance or, alternatively, may be due to taxon-specific changes (Palmer et al., 2011, 2013). At present, the comparative roles of photoacclimation and the taxonomic components in determining carbon fixation characteristics could not be elucidated. Sources of error in our productivity estimates include uncertainties related to the vertical chl a distribution and that our sampling scheme did not account for photoacclimation, which can influence carbon fixation characteristics in stratified systems.

In conclusion, nitrate limitation assays revealed increasing N limitation in the surface waters of central Kongsfjorden in June, coinciding with increasing strati-fication strength. N limitation was followed by a change in taxonomic composition and size structure of the phy-toplankton community, suggesting that N limitation was

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a driver of taxonomic succession in Kongsfjorden post-bloom phytoplankton. However, the complete change in phytoplankton composition in the current study was not accompanied by trends in surface water chl a or water col-umn productivity. Furthermore, we observed differences in surface nutrient concentrations between central and inner Kongsfjorden, presumably due to upwelling in the proximity of the glacier front and subsequent episodic wind-induced transport out of the fjord. Therefore, nutri-ent limitation appeared to be less pronounced in inner as compared to central Kongsfjorden. Our investigation sug-gests that glacial meltwater has contrasting effects on phy-toplankton on temporal and spatial scales by influencing both stratification and upwelling processes. Summertime stratification by glacial meltwater influx, melting sea ice, and/or terrestrial runoff from snow and ice melt is an annually occurring process in Kongsfjorden (Hop et al., 2002). Glacial calving has previously been shown to be gov-erned by seawater temperature in Kongsfjorden (Luckman et al., 2015), so that years with strong Atlantic advection can be expected to have a stronger summertime glacial meltwater component governing stratification (Fransson et al., 2016). Consequently, years with stronger Atlantic advection and stronger summertime stratification may experience a stronger shift in post-bloom phytoplankton community and size structure in central Kongsfjorden. However, warming of the fjord may also increase nutrient upwelling near the glaciers due to elevated glacial meltwa-ter discharge. Whether this scenario also causes a stronger contrast between inner and central Kongsfjorden remains to be elucidated. The observed environmental changes in Kongsfjorden of the past decades have the potential to influence nutrient limitation, phytoplankton composi-tion, and thereby higher trophic levels, making these pro-cesses and their relation to stratification in Kongsfjorden deserving of further investigation.

Data Accessibility Statementhttps://doi.pangaea.de/10.1594/PANGAEA.878242.

Supplemental filesThe supplemental files for this article can be found as follows:

• Table S1. Initial (A) and final (B) pigment ratios for CHEMTAX taxonomic groups relative to chlorophyll a. DOI: https://doi.org/10.1525/elementa.307.s1

• Figure S1. Salinity, temperature and reconstructed chl a profiles. DOI: https://doi.org/10.1525/elementa.307.s1

• Figure S2. Irradiance and productivity profiles. DOI: https://doi.org/10.1525/elementa.307.s1

• Figure S3. NMDS of phytoplankton composition. DOI: https://doi.org/10.1525/elementa.307.s1

AcknowledgementsWe thank the technical and scientific staff of the Alfred Wegener Institute for facilitating our research at the AWIPEV research base, and for providing the meteoro-logical data. Furthermore, we thank the Kingsbay Marine lab staff for their assistance. Special thanks to Loes A. H. Venekamp for the light microscopy analysis.

Funding informationsThis work is a contribution to NWO project 866.12.408 (Buma) and 866.12.404 (Brussaard).

Competing interestsThe authors have no competing interests to declare.

Author contributions• WHvdP: contributed to design, data acquisition,

analysis and interpretation.• GK: contributed to data acquisition, analysis and

interpretation.• PDR: contributed to analysis and interpretation.• CPDB: contributed to analysis and interpretation.• RJWV: contributed to analysis and interpretation.• AGJB: contributed to analysis and interpretation.

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How to cite this article: van de Poll, WH, Kulk, G, Rozema, PD, Brussaard, CPD, Visser, RJW and Buma, AGJ. 2018. Contrasting glacial meltwater effects on post-bloom phytoplankton on temporal and spatial scales in Kongsfjorden, Spitsbergen. Elem Sci Anth, 6: 50. DOI: https://doi.org/10.1525/elementa.307

Domain Editor-in-Chief: Jody W. Deming, Ph.D., Department of Biological Oceanography, University of Washington, US

Associate Editor: Jean-Éric Tremblay, Department of Biology, Université Laval, CA

Knowledge Domain: Ocean Science

Submitted: 27 July 2017 Accepted: 21 June 2018 Published: 10 July 2018

Copyright: © 2018 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/. OPEN ACCESS Elem Sci Anth is a peer-reviewed open access

journal published by University of California Press.